Voltage imaging and optogenetics offer new routes to optically detect and influence neural dynamics. Optimized hardware is necessary to make the most of these new techniques. Here we present the Octoscope, a versatile, multimodal device for all-optical electrophysiology. We illustrate its concept and design and demonstrate its capability to perform both 1-photon and 2-photon voltage imaging with spatial and temporal light patterning, in both inverted and upright configurations, in vitro and in vivo.

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Microtubule (MT)-associated protein 7 (MAP7) is a required cofactor for kinesin-1-driven transport of intracellular cargoes. Using cryo-electron microscopy and single-molecule imaging, we investigated how MAP7 binds MTs and facilitates kinesin-1 motility. The MT-binding domain (MTBD) of MAP7 bound MTs as an extended a helix between the protofilament ridge and the site of lateral contact. Unexpectedly, the MTBD partially overlapped with the binding site of kinesin-1 and inhibited its motility. However, by tethering kinesin-1 to the MT, the projection domain of MAP7 prevented dissociation of the motor and facilitated its binding to available neighboring sites. The inhibitory effect of the MTBD dominated as MTs became saturated with MAP7. Our results reveal biphasic regulation of kinesin-1 by MAP7 in the context of their competitive binding to MTs.

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Summary: We present a fast particle fusion method for particles imaged with single-molecule localization microscopy. The state-of-the-art approach based on all-to-all registration has proven to work well but its computational cost scales unfavorably with the number of particles N, namely as N2. Our method overcomes this problem and achieves a linear scaling of computational cost with N by making use of the Joint Registration of Multiple Point Clouds (JRMPC) method. Straightforward application of JRMPC fails as mostly locally optimal solutions are found. These usually contain several overlapping clusters that each consist of well-aligned particles, but that have different poses. We solve this issue by repeated runs of JRMPC for different initial conditions, followed by a classification step to identify the clusters, and a connection step to link the different clusters obtained for different initializations. In this way a single well-aligned structure is obtained containing the majority of the particles. Results: We achieve reconstructions of experimental DNA-origami datasets consisting of close to 400 particles within only 10 min on a CPU, with an image resolution of 3.2 nm. In addition, we show artifact-free reconstructions of symmetric structures without making any use of the symmetry. We also demonstrate that the method works well for poor data with a low density of labeling and for 3D data.

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Particle fusion for single molecule localization microscopy improves signal-to-noise ratio and overcomes underlabeling, but ignores structural heterogeneity or conformational variability. We present a-priori knowledge-free unsupervised classification of structurally different particles employing the Bhattacharya cost function as dissimilarity metric. We achieve 96% classification accuracy on mixtures of up to four different DNA-origami structures, detect rare classes of origami occuring at 2% rate, and capture variation in ellipticity of nuclear pore complexes.@en